Files
gonum/graph/formats/rdf/equi_canonical.go
2021-09-28 08:29:48 +09:30

577 lines
13 KiB
Go
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

// Copyright ©2021 The Gonum Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package rdf
import (
"errors"
"sort"
)
// Throughout, the comments refer to doi:10.1145/3068333 which should be
// understood as a synonym for http://aidanhogan.com/docs/rdf-canonicalisation.pdf
// although there are differences between the two, see http://aidanhogan.com/#errataH17.
// Where there are differences, the document at http://aidanhogan.com/ is the
// canonical truth. The DOI reference is referred to for persistence.
// Lean returns an RDF core of g that entails g. If g contains any non-zero
// labels, Lean will return a non-nil error and a core of g assuming no graph
// labels exist.
//
// See http://aidanhogan.com/docs/rdf-canonicalisation.pdf for details of
// the algorithm.
func Lean(g []*Statement) ([]*Statement, error) {
// BUG(kortschak): Graph leaning does not take into account graph label terms
// since the formal semantics for a multiple graph data model have not been
// defined. See https://www.w3.org/TR/rdf11-datasets/#declaring.
var (
hasBlanks bool
err error
)
for _, s := range g {
if isBlank(s.Subject.Value) || isBlank(s.Object.Value) {
hasBlanks = true
if err != nil {
break
}
}
if s.Label.Value != "" && err == nil {
err = errors.New("rdf: data-set contains graph names")
if hasBlanks {
break
}
}
}
if hasBlanks {
g = lean(&dfs{}, g)
}
return g, err
}
// removeRedundantBnodes removes blank nodes whose edges are a subset of
// another term in the RDF graph.
//
// This is algorithm 4 in doi:10.1145/3068333.
func removeRedundantBnodes(g []*Statement) []*Statement {
g = append(g[:0:0], g...)
for {
edges := make(map[string]map[triple]bool)
for _, s := range g {
for i, t := range []string{
s.Subject.Value,
s.Object.Value,
} {
e, ok := edges[t]
if !ok {
e = make(map[triple]bool)
edges[t] = e
}
switch i {
case 0:
e[triple{s.Predicate.Value, s.Object.Value, "+"}] = true
case 1:
e[triple{s.Predicate.Value, s.Subject.Value, "-"}] = true
}
}
}
seen := make(map[string]bool)
bNodes := make(map[string]bool)
terms := make(map[string]bool)
for _, s := range g {
for _, t := range []string{
s.Subject.Value,
s.Predicate.Value,
s.Object.Value,
} {
terms[t] = true
if isBlank(t) {
bNodes[t] = true
} else {
seen[t] = true
}
}
}
redundant := make(map[string]bool)
for x := range bNodes {
for xp := range terms {
if isProperSubset(edges[x], edges[xp]) || (seen[xp] && isEqualEdges(edges[x], edges[xp])) {
redundant[x] = true
break
}
}
seen[x] = true
}
n := len(g)
for i := 0; i < len(g); {
if !redundant[g[i].Subject.Value] && !redundant[g[i].Object.Value] {
i++
continue
}
g[i], g = g[len(g)-1], g[:len(g)-1]
}
if n == len(g) {
return g
}
}
}
type triple [3]string
func isProperSubset(a, b map[triple]bool) bool {
for k := range a {
if !b[k] {
return false
}
}
return len(a) < len(b)
}
func isEqualEdges(a, b map[triple]bool) bool {
if len(a) != len(b) {
return false
}
for k := range a {
if !b[k] {
return false
}
}
return true
}
// findCandidates finds candidates for blank nodes and blank nodes that are fixed.
//
// This is algorithm 5 in doi:10.1145/3068333.
func findCandidates(g []*Statement) ([]*Statement, map[string]bool, map[string]map[string]bool, bool) {
g = removeRedundantBnodes(g)
edges := make(map[triple]bool)
f := make(map[string]bool)
for _, s := range g {
sub := s.Subject.Value
prd := s.Predicate.Value
obj := s.Object.Value
edges[triple{sub, prd, obj}] = true
edges[triple{sub, prd, "*"}] = true
edges[triple{"*", prd, obj}] = true
switch {
case isBlank(sub) && isBlank(obj):
f[sub] = false
f[obj] = false
case isBlank(sub):
if _, ok := f[sub]; !ok {
f[sub] = true
}
case isBlank(obj):
if _, ok := f[obj]; !ok {
f[obj] = true
}
}
}
for k, v := range f {
if !v {
delete(f, k)
}
}
if len(f) == 0 {
f = nil
}
cands := make(map[string]map[string]bool)
bnodes := make(map[string]bool)
for _, s := range g {
for _, b := range []string{
s.Subject.Value,
s.Object.Value,
} {
if !isBlank(b) {
continue
}
bnodes[b] = true
if f[b] {
cands[b] = map[string]bool{b: true}
} else {
terms := make(map[string]bool)
for _, s := range g {
for _, t := range []string{
s.Subject.Value,
s.Predicate.Value,
s.Object.Value,
} {
terms[t] = true
}
}
cands[b] = terms
}
}
}
if isEqualTerms(f, bnodes) {
return g, f, cands, true
}
for {
bb := make(map[string]bool)
for b := range bnodes {
if !f[b] {
bb[b] = true
}
}
for b := range bb {
for x := range cands[b] {
if x == b {
continue
}
for _, s := range g {
if s.Subject.Value != b {
continue
}
prd := s.Predicate.Value
obj := s.Object.Value
if (inILF(obj, f) && !edges[triple{x, prd, obj}]) || (bb[obj] && !edges[triple{x, prd, "*"}]) {
delete(cands[b], x)
break
}
}
if !cands[b][x] {
continue
}
for _, s := range g {
if s.Object.Value != b {
continue
}
sub := s.Subject.Value
prd := s.Predicate.Value
if (inIF(sub, f) && !edges[triple{sub, prd, x}]) || (bb[sub] && !edges[triple{"*", prd, x}]) {
delete(cands[b], x)
break
}
}
}
}
fp := f
f = make(map[string]bool)
for b := range fp {
f[b] = true
}
for b := range bb { // Mark newly fixed blank nodes.
if len(cands[b]) == 1 && cands[b][b] {
f[b] = true
}
}
allFixed := isEqualTerms(f, bnodes)
if isEqualTerms(fp, f) || allFixed {
if len(f) == 0 {
f = nil
}
return g, f, cands, allFixed
}
}
}
// inILF returns whether t is in IL or F.
func inILF(t string, f map[string]bool) bool {
return isIRI(t) || isLiteral(t) || f[t]
}
// inIF returns whether t is in I or F.
func inIF(t string, f map[string]bool) bool {
return isIRI(t) || f[t]
}
// dfs is a depth-first search strategy.
type dfs struct{}
// lean returns a core of the RDF graph g using the given strategy.
//
// This is lines 1-9 of algorithm 6 in doi:10.1145/3068333.
func lean(strategy *dfs, g []*Statement) []*Statement {
foundBnode := false
search:
for _, s := range g {
for _, t := range []string{
s.Subject.Value,
s.Object.Value,
} {
if isBlank(t) {
foundBnode = true
break search
}
}
}
if !foundBnode {
return g
}
g, fixed, cands, allFixed := findCandidates(g)
if allFixed {
return g
}
for _, s := range g {
if isBlank(s.Subject.Value) && isBlank(s.Object.Value) {
mu := make(map[string]string, len(fixed))
for b := range fixed {
mu[b] = b
}
mu = findCoreEndomorphism(strategy, g, cands, mu)
return applyMu(g, mu)
}
}
return g
}
// findCoreEndomorphism returns a core solution using the given strategy.
//
// This is lines 10-14 of algorithm 6 in doi:10.1145/3068333.
func findCoreEndomorphism(strategy *dfs, g []*Statement, cands map[string]map[string]bool, mu map[string]string) map[string]string {
var q []*Statement
preds := make(map[string]int)
seen := make(map[triple]bool)
for _, s := range g {
preds[s.Predicate.Value]++
if isBlank(s.Subject.Value) && isBlank(s.Object.Value) {
if seen[triple{s.Subject.Value, s.Predicate.Value, s.Object.Value}] {
continue
}
seen[triple{s.Subject.Value, s.Predicate.Value, s.Object.Value}] = true
q = append(q, s)
}
}
sort.Slice(q, func(i, j int) bool {
return selectivity(q[i], cands, preds) < selectivity(q[j], cands, preds)
})
return strategy.evaluate(g, q, cands, mu)
}
// selectivity returns the selectivity heuristic score for s. Lower scores
// are more selective.
func selectivity(s *Statement, cands map[string]map[string]bool, preds map[string]int) int {
return min(len(cands[s.Subject.Value])*len(cands[s.Object.Value]), preds[s.Predicate.Value])
}
// evaluate returns an endomorphism using a DFS strategy.
//
// This is lines 25-32 of algorithm 6 in doi:10.1145/3068333.
func (st *dfs) evaluate(g, q []*Statement, cands map[string]map[string]bool, mu map[string]string) map[string]string {
mu = st.search(g, q, cands, mu)
for len(mu) != len(codom(mu)) {
mupp := fixedFrom(cands)
mup := findCoreEndomorphism(st, applyMu(g, mu), cands, mupp)
if isAutomorphism(mup) {
return mu
}
for b, x := range mu {
if _, ok := mup[b]; !ok {
mup[b] = x
}
}
mu = mup
}
return mu
}
func fixedFrom(cands map[string]map[string]bool) map[string]string {
fixed := make(map[string]string)
for b, m := range cands {
if len(m) == 1 && m[b] {
fixed[b] = b
}
}
return fixed
}
// applyMu applies mu to g returning the result.
func applyMu(g []*Statement, mu map[string]string) []*Statement {
back := make([]Statement, 0, len(g))
dst := make([]*Statement, 0, len(g))
seen := make(map[Statement]bool)
for _, s := range g {
n := Statement{
Subject: Term{Value: translate(s.Subject.Value, mu)},
Predicate: Term{Value: s.Predicate.Value},
Object: Term{Value: translate(s.Object.Value, mu)},
Label: Term{Value: s.Label.Value},
}
if seen[n] {
continue
}
seen[n] = true
back = append(back, n)
dst = append(dst, &back[len(back)-1])
}
return dst
}
// search returns a minimum endomorphism using a DFS strategy.
//
// This is lines 33-46 of algorithm 6 in doi:10.1145/3068333.
func (st *dfs) search(g, q []*Statement, cands map[string]map[string]bool, mu map[string]string) map[string]string {
qMin := q[0]
m := st.join(qMin, g, cands, mu)
if len(m) == 0 {
// Early exit if no mapping found.
return nil
}
sortByCodom(m)
mMin := m[0]
qp := q[1:]
if len(qp) != 0 {
for len(m) != 0 {
mMin = m[0]
mup := st.search(g, qp, cands, mMin)
if !isAutomorphism(mup) {
return mup
}
m = m[1:]
}
}
return mMin
}
// isAutomorphism returns whether mu is an automorphism, this is equivalent to
// dom(mu) == codom(mu).
func isAutomorphism(mu map[string]string) bool {
return isEqualTerms(dom(mu), codom(mu))
}
// dom returns the domain of mu.
func dom(mu map[string]string) map[string]bool {
d := make(map[string]bool, len(mu))
for v := range mu {
d[v] = true
}
return d
}
// codom returns the codomain of mu.
func codom(mu map[string]string) map[string]bool {
cd := make(map[string]bool, len(mu))
for _, v := range mu {
cd[v] = true
}
return cd
}
// isEqualTerms returns whether a and b are identical.
func isEqualTerms(a, b map[string]bool) bool {
if len(a) != len(b) {
return false
}
for k := range a {
if !b[k] {
return false
}
}
return true
}
// sortByCodom performs a sort of maps ordered by fewest blank nodes in
// codomain, then fewest self mappings.
func sortByCodom(maps []map[string]string) {
m := orderedByCodom{
maps: maps,
attrs: make([]attrs, len(maps)),
}
for i, mu := range maps {
m.attrs[i].blanks = make(map[string]bool)
for x, y := range mu {
if isBlank(y) {
m.attrs[i].blanks[y] = true
}
if x == y {
m.attrs[i].selfs++
}
}
}
sort.Sort(m)
}
type orderedByCodom struct {
maps []map[string]string
attrs []attrs
}
type attrs struct {
blanks map[string]bool
selfs int
}
func (m orderedByCodom) Len() int { return len(m.maps) }
func (m orderedByCodom) Less(i, j int) bool {
attrI := m.attrs[i]
attrJ := m.attrs[j]
switch {
case len(attrI.blanks) < len(attrJ.blanks):
return true
case len(attrI.blanks) > len(attrJ.blanks):
return false
default:
return attrI.selfs < attrJ.selfs
}
}
func (m orderedByCodom) Swap(i, j int) {
m.maps[i], m.maps[j] = m.maps[j], m.maps[i]
m.attrs[i], m.attrs[j] = m.attrs[j], m.attrs[i]
}
// join evaluates the given pattern, q, joining with solutions in m.
// This takes only a single mapping and so only works for the DFS strategy.
//
// This is lines 47-51 of algorithm 6 in doi:10.1145/3068333.
func (st *dfs) join(q *Statement, g []*Statement, cands map[string]map[string]bool, m map[string]string) []map[string]string {
var mp []map[string]string
isLoop := q.Subject.Value == q.Object.Value
for _, s := range g {
// Line 45: M_q ← {µ | µ(q) ∈ G}
// | µ(q) ∈ G
//
// µ(q) ∈ G ↔ (µ(q_s),q_p,µ(q_o)) ∈ G
if q.Predicate.Value != s.Predicate.Value {
continue
}
// q_s = q_o ↔ µ(q_s) =_µ(q_o)
if isLoop && s.Subject.Value != s.Object.Value {
continue
}
// Line 46: M_q' ← {µ ∈ M_q | for all b ∈ bnodes({q}), µ(b) ∈ cands[b]}
// | for all b ∈ bnodes({q}), µ(b) ∈ cands[b]
if !cands[q.Subject.Value][s.Subject.Value] || !cands[q.Object.Value][s.Object.Value] {
continue
}
// Line 47: M' ← M_q' ⋈ M
// M₁ ⋈ M₂ = {μ₁ μ₂ | μ₁ ∈ M₁, μ₂ ∈ M₂ and μ₁, μ₂ are compatible mappings}
// | μ₁ ∈ M₁, μ₂ ∈ M₂ and μ₁, μ₂ are compatible mappings
if mq, ok := m[q.Subject.Value]; ok && mq != s.Subject.Value {
continue
}
if !isLoop {
if mq, ok := m[q.Object.Value]; ok && mq != s.Object.Value {
continue
}
}
// Line 47: μ₁ μ₂
var mu map[string]string
if isLoop {
mu = map[string]string{
q.Subject.Value: s.Subject.Value,
}
} else {
mu = map[string]string{
q.Subject.Value: s.Subject.Value,
q.Object.Value: s.Object.Value,
}
}
for b, mb := range m {
mu[b] = mb
}
mp = append(mp, mu)
}
return mp
}